System and method to identify sources associated with biological rhythm disorders

ABSTRACT

A system and method are provided to define a driver of a source associated with a cardiac rhythm disorder of a human heart. A plurality of cardiac signals associated with sensors arranged spatially in relation to an area of the heart are processed to determine a sequence of arcs of rotation in relation to the sensors over a time interval. Rotational directions of the arcs of rotation in the sequence are determined. The area of the heart is identified as controlling the source when the rotational directions of the arcs of rotation in the sequence continue in a same rotational direction in excess of a threshold.

RELATED APPLICATIONS

This application is a continuation of application Ser. No. 14/774,120,filed Sep. 9, 2015, which is a 371 national stage filing ofInternational Application No. PCT/US2014/029645, filed Mar. 14, 2014,which claims the benefit of the priority of U.S. application Ser. No.13/844,562, now U.S. Pat. No. 9,332,915, filed Mar. 15, 2013, which isincorporated herein by reference in its entirety.

GOVERNMENT RIGHTS

This invention was made with government support under Grants R01 HL83359and HL103800 from the National Institutes of Health. The government hascertain rights in the invention.

BACKGROUND

Field of the Disclosure

The present application relates generally to biological rhythmdisorders. More specifically, the present application is directed to asystem and method to define drivers of sources associated withbiological rhythm disorders, such as heart rhythm disorders.

Brief Discussion of Related Art

Heart (cardiac) rhythm disorders are common and represent significantcauses of morbidity and death throughout the world. Malfunction of theelectrical system in the heart represents a proximate cause of heartrhythm disorders. Heart rhythm disorders exist in many forms, of whichthe most complex and difficult to treat are atrial fibrillation (AF),ventricular tachycardia (VT) and ventricular fibrillation (VF). Otherrhythm disorders, which are easier to treat, but which may also beclinically significant, include atrial tachycardia (AT),supraventricular tachycardia (SVT), atrial flutter (AFL),supraventricular ectopic complexes/beats (SVE) and premature ventricularcomplexes/beats (PVC). While under normal conditions the sinus nodekeeps the heart in sinus rhythm, under certain conditions rapidactivation of the normal sinus node can cause inappropriate sinustachycardia or sinus node reentry, both of which also represent heartrhythm disorders.

Previously, treatment of heart rhythm disorders—particularly complexrhythm disorders of AF, VF and polymorphic VT—has been difficult becausethe location in the heart that harbors the source of the heart rhythmdisorder could not be identified. There have been various theories ofhow complex rhythm disorders function and clinical applications fortreating these complex rhythm disorders. However, none of theapplications proved fruitful in the treatment of complex rhythmdisorders.

Recently, there has been a breakthrough discovery that for the firsttime identified sources associated with complex heart rhythm disorders.This technological breakthrough successfully reconstructed cardiacactivation information (onset times) in signals obtained from electrodesof catheters introduced into patients' heart to identify rotationalactivation patterns (rotational sources) or centrifugal patterns (focalsources) that cause a large percentage of the heart rhythm disordersworldwide. Treatment of the heart rhythm disorders can thus be targetedto these rotational or focal sources in the patients' heart to eliminatethe heart rhythm disorders. Such treatment can be successfully deliveredby ablation, for example.

While a rotational or focal source of a complex heart rhythm disordercan be identified as described above, the inner mechanism of thesource—i.e., the core of the rotational source (its likely center ofrotation), or origin of a focal source—are not well defined. In someinstances, a rotational source may have one or more diffuse sections(activation wave fronts) that generally appear to rotate around asubjective rotation center, but tend to spread out diffusely about asection of the patient's heart. While the diffuse activation wave frontsare associated with the source of the complex rhythm disorder, they maycontribute insignificantly to driving the heart rhythm disorder than oneor more other activation wave fronts of the rotational source.Similarly, the core of a centrifugally emanating focal source of acomplex rhythm disorder has not been well defined.

It has thus far been undefined how to identify the core of a rotationalsource in contrast to an insignificant ‘passive’ rotation that is not asource of the heart rhythm disorder, or how to identify the origin of atrue focal source in contrast to an occasional focal activation that canbe secondary to a complex rhythm disorder, rather than its source.

There are no known systems or methods to define the core of a rotationalsource or the origin of a focal source associated with a heart rhythmdisorder.

SUMMARY

In accordance with an embodiment or aspect, a method of identifying adriver of a source associated with a heart rhythm disorder is disclosed.Data is accessed from a plurality of sensors representing biologicalactivity in the heart. A local first region of the heart that hasrepeating activation and that controls a second distant region of theheart for at least a predetermined number of beats is identified. Thefirst local region is assigned as a driver of a source of the heartrhythm disorder, the source including the first local region and thesecond distant region.

In accordance with another embodiment or aspect, a system of identifyinga driver of a source associated with a heart rhythm disorder isdisclosed. The system includes a processor and a storage medium storinginstructions that, when executed by the processor, cause the processorto perform certain operations. The operations include accessing datafrom a plurality of sensors representing biological activity in theheart. The operations also include identifying a local first region ofthe heart that has repeating activation and that controls a seconddistant region of the heart for at least a predetermined number ofbeats. The operations further include assigning the first local regionas a driver of a source of the heart rhythm disorder, the sourceincluding the first local region and the second distant region.

In accordance with yet another embodiment or aspect, a method ofidentifying an area of a human heart associated with controlling asource of a cardiac rhythm disorder is disclosed. A plurality of cardiacsignals, associated with sensors arranged spatially in relation to thearea of the heart, is processed to determine at least one sequence ofactivation in relation to the sensors over a time interval. A rotationaldirection of the at least one sequence of activation is determined. Thearea of the heart is identifies as associated with controlling thesource when the at least one sequence of activation continues to rotatein the rotational direction over the time interval.

In accordance with a further embodiment or aspect, a system to identifyan area of a human heart associated with controlling a source of acardiac rhythm disorder is disclosed. The system includes a processingdevice and a memory device storing instructions that, when executed bythe processing device, cause the processing device to perform certainoperations. The operations include processing a plurality of cardiacsignals associated with sensors arranged spatially in relation to thearea of the heart to determine at least one sequence of activation inrelation to the sensors over a time interval. The operations alsoinclude determining a rotational direction of the at least one sequenceof activation. The operations further include identifying the area ofthe heart as associated with controlling the source when the at leastone sequence of activation continues to rotate in the rotationaldirection over the time interval.

In accordance with still another embodiment or aspect, a method todefine a driver of a source associated with a cardiac rhythm disorder ofa human heart is disclosed. A plurality of cardiac signals associatedwith sensors arranged spatially in relation to an area of the heart isprocessed to determine a sequence of arcs of rotation in relation to thesensors over a time interval. Rotational directions of the arcs ofrotation in the sequence are determined. The area of the heart isidentified as a driver of the source when the rotational directions ofthe arcs of rotation in the sequence continue in a same rotationaldirection in access of a threshold.

In accordance with still a further embodiment or aspect, a system todefine a driver of a source associated with a cardiac rhythm disorder ofa human heart is disclosed. The system includes a processing device anda memory device storing instructions that, when executed by theprocessing device, cause the processing device to perform certainoperations. The operations include processing a plurality of cardiacsignals associated with sensors arranged spatially in relation to anarea of the heart to determine a sequence of arcs of rotation inrelation to the sensors over a time interval. The operations alsoinclude determining rotational directions of the arcs of rotation in thesequence. The operations further include identifying the area of theheart as a driver of the source when the rotational directions of thearcs of rotation in the sequence continue in a same rotational directionin excess of a threshold.

These and other purposes, goals and advantages of the presentapplication will become apparent from the following detailed descriptionread in connection with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Some embodiments or aspects are illustrated by way of example and notlimitation in the figures of the accompanying drawings in which likenumbers refer to like parts and in which:

FIG. 1 illustrates a system to identify rotational patterns orcentrifugal patterns indicating activation emanation from localizedsources for heart rhythm disorders;

FIG. 2 illustrates an example phase-time curve related to electricalsignals sensed by a sensor positioned in relation to a heart illustratedin FIG. 1;

FIG. 3 illustrates another example phase-time curve related toelectrical signals sensed by a sensor positioned in relation to theheart illustrated in FIG. 1;

FIG. 4 illustrates a grid with sensing elements related to locations ofsensors illustrated in FIG. 1;

FIG. 5 illustrates a first example unit circle showing sensor elementsillustrated in FIG. 4 with a first set of phase values;

FIG. 6 illustrates a second example unit circle showing the sensorelements illustrated in FIG. 4 with a second set of different phasevalues;

FIG. 7 illustrates a flowchart that shows an example method for summing(counting) indexes of rotational activity or centrifugal activationassociated with a localized driver associated with areas of the gridillustrated in FIG. 4 over a time interval;

FIG. 8 illustrates a flowchart that shows an example method for summingan index of driver activity within an area of the grid illustrated inFIG. 7;

FIG. 9 illustrates a heat map, which indicates the persistence of arotational driver (illustrated) or focal driver associated with a sourceof the heart rhythm disorder, and which is superimposed on an activationpropagation map; and

FIG. 10 illustrates a block diagram of an illustrative embodiment of ageneral computer system.

DETAILED DESCRIPTION

A system and method for defining drivers of sources associated withheart rhythm disorders are disclosed herein. In the followingdescription, for the purposes of explanation, numerous specific detailsare set forth in order to provide a thorough understanding of exampleembodiments or aspects. It will be evident, however, to one skilled inthe art, that an example embodiment may be practiced without all of thedisclosed specific details.

The present disclosure is applicable to defining various drivers ofsources associated with heart rhythm disorders. Drivers may berepresented by persistent rotational activation around a center that mayshow movement (‘meander’ or ‘precession’), or persistently repetitiveactivation from an origin. The disclosure can also be applied to otherbiological rhythm disorders, such as neurological seizures, esophagealspasms, bladder instability, irritable bowel syndrome, and otherbiological disorders for which biological activation information can bereconstructed to permit determination, diagnosis, and/or treatment ofthe cause or source of the disorders. It is particularly useful,however, in complex rhythm disorders which result in complex activationpatterns, and especially useful in complex rhythm disorders of the heartsuch as atrial fibrillation, ventricular fibrillation and others, inorder to find the driver(s) associated with source(s) of the complexrhythm disorders such that they can be treated with expediency.

Complex heart rhythm disorders, including but not limited to atrialfibrillation, polymorphic atrial tachycardia, ventricular fibrillation,polymorphic ventricular tachycardia and others, typically result inactivation patterns that are extremely difficult to decipher.

A novel concept is that activation from a localized region of the heartmust activate surrounding tissue during the heart rhythm disorder bydefinition, even for complex heart rhythm disorders. This control mayproceed via a centrifugal activation from the local region tosurrounding tissue, or by rotational (rotor) activation from the localregion to surrounding tissue. The localized region (driver) for complexrhythm disorders generally occupies an area. This disclosure describesfor the first time that the driver within a localized region maydemonstrate activation sequences that are rotational or centrifugal,which may affect or control a remote region of the heart.

Thus, to identify or define the local region of a complex heart rhythmdisorder, it is essential not just to identify its rotational orcentrifugal driver, but it is also necessary to ensure that the drivercontrols activation in a distant region of the heart. These criteriacan, therefore, help to eliminate many spurious or unimportant ‘spins’or ‘focal discharges’ uncovered in the current state of the art that arenot drivers of the sources associated with heart rhythm disorders, andcan help to improve treatment where localized therapy has not beensuccessful in the past.

The ability to determine accurate activation information of heart beatsin complex disorders has previously been very difficult, such thattargeted therapy aimed at the source(s) of these disorders has not beenpossible. Among the advantages of the present disclosure is the abilityto recognize rotational electrical patterns, even amidst the virtuallyindiscernible sensed activation patterns, such that a determination ofthe source of the disorder can be determined and treated.

Complex rhythm disorders are directly caused by localized sources, fromwhence activation may take the form of spiral waves with rotationalelectrical activity, focal sources in which activation emanatescentrifugally or a combination. The complexity of multiple concurrentdrivers can cause disorganized activation patterns (sources), which haveobscured prior attempts to map these rhythms. In this way, passiveactivation from colliding or secondary wave fronts may transientlyobscure the detection of the source of the disorder, but not terminateits internal driver. In electrophysiological terms, this is similar topacing ‘entrainment’ transiently altering activation sequences around adriver (e.g., in the Wolff-Parkinson-White syndrome or atrial flutter),with redetection of the driver when entrainment stops. The presentdisclosure shows that this is also true for detection of drivers ofsources associated with complex rhythm disorders.

Accordingly, rotational electrical activity from a spiral wave (rotor,reentrant circuit) may appear to be insignificant, either in the degreeor duration of the rotation, or have inconsistent rotation patterns. Ithas previously been unclear how to separate sources from transientactivation of an occasional rotation or single cycle where activationappears to emanate from an origin, inherent in all complex rhythms. Thistask has been more difficult since sources for complex rhythms are notpoints, but occupy limited spatial areas within which the driver maymove (termed “meander” or “precession”)—akin to the movement of aspinning object in a gravity well.

The present disclosure provides a system and method for defining oridentifying persistent rotational drivers or focal drivers withinlocalized sources associated with complex rhythm disorders. Rotationaldrivers can be defined or identified by showing that activationsequences trace successive angles, or show successive angular sectorsover time, or using phase mapping, vector analysis and other methods.Focal drivers can be identified by vectors, coherence, correlation,phase and other analytic methods to identify centrifugal activation froman origin. Additionally, the system and method of the present disclosureprovide qualitative and/or quantitative indicators to indicate thestrength, consistency, and duration of identified phase singularities.

Another advantage is that the present disclosure provides a system andmethod that can be carried out rapidly while a sensing device, e.g., acatheter having sensors thereon, is used in or near the patient and canbe followed by treatment of cardiac tissue to ameliorate the disorderand in many cases cure the disorder. Treatment may thus occurimmediately upon computing the rotational electrical pattern informationof the driver of the source, since it will indicate the location(s) ofthe cause or source of the disorder.

FIG. 1 illustrates an example system for identifying the driver (an areaof the heart) associated with the source of a heart rhythm disorder 100.The example system 100 is configured to identify a driver, in the formof persistent rotational or centrifugal patterns, associated with sensedcardiac electrical activity of a patient's heart 120 in connection withdetermining the source of a heart rhythm disorder. The heart 120includes a right atrium 122, left atrium 124, right ventricle 126 andleft ventricle 128.

The example system 100 includes a catheter 102, signal processing device114, computing device 116 and analysis database 118. The catheter 102 isconfigured to detect cardiac electrical information in the heart and totransmit the detected cardiac electrical information to the signalprocessing device 114, either via a wireless or wired connection. Thecatheter includes an array of probes/sensors 104, which can be insertedinto the heart through the patient's blood vessels. Sensors 104 mayprovide unipolar and/or bipolar signals.

In some embodiments or aspects, one or more of the sensors 104 are notinserted into the patient's heart 120. For example, some sensors maydetect cardiac electrical information via the patient's surface (e.g.,electrocardiogram) or remotely without contact with the patient (e.g.,magnetocardiogram or methods to identify electrical information via theinverse solution). As another example, some sensors may also derivecardiac electrical information from cardiac motion of a non-electricalsensing device (e.g., echocardiogram). In various embodiments oraspects, these sensors can be used separately or in differentcombinations, and further these separate or different combinations canalso be used in combination with sensors inserted into the patient'sheart 120.

The sensors 104 are positioned at respective sensor locations adjacentto or contacting tissue in the heart 120 or near the heart 120. Thesensors 104 can detect cardiac electrical activity at the sensorlocations and can generate corresponding sensing signals which areoutput to the signal processing device 114. The sensors 104 may furtherbe configured to deliver energy to ablate the heart 120 at the sensorlocations, particularly when the sensor location is adjacent to orcontacting heart tissue.

The signal processing device 114 is configured to process (e.g., clarifyand amplify) the sensing signals generated by the sensors 104 and tooutput corresponding cardiac signals. The computing device 116 receives(which refers to receiving or accessing) the cardiac signals andprocesses them in accordance with methods disclosed herein to identifyrotational electrical activity (clockwise or counterclockwise) orcentrifugal activity (indicating a focal driver) from the cardiacsignals. Additionally, the computing device 116 identifies indices ofdriver activity that are persistent.

The computing device 116 displays an activation propagation map (APM)video 150 that combines and spatially lays out data from a plurality ofmonophasic action potential (MAP) voltage representations of the cardiacsignals. The APM video 150 includes a sequence of APM frames that areassociated with a series of time increments over a time interval. Arrow152 indicates rotational movement of displayed information. Each elementin the MAP representation is associated with a respective sensor 104 ofthe array of sensors. A MAP representation includes voltage (or charge)versus time and other indexes. For rotational drivers, detection mayalso use information on rotational angles, solid angles, angularvelocity, and tangential velocity at the circumference of rotation andphase information. For focal sources, information may also includecentrifugal indexes (such as velocity and acceleration), and centripetalindexes (such as velocity and acceleration). Centripetal indexestypically indicate a passive area (not a source), but may indicate asource that is moving away from the sensor. For all sources,quantification includes stigmata of dynamic movement such as Dopplershift, disorganization in the core, and measures of entropy since thedriver may move constantly and dynamically within the source region.Information may also include activation onset time informationassociated with the electrical activity sensed by a sensor 104 of thearray of sensors. The MAP representation can be mapped as curves on timeand voltage axes, as well as several other representations includingpolar plots and three-dimensional plots.

As used herein, activation onset time is a time point at whichactivation commences in a cell or tissue, as opposed to other timepoints during activation. Activation is a process whereby a cellcommences its operation from a quiescent (diastolic) state to an active(electrical) state.

The computing device 116 receives, accesses, or generates the signalrepresentations and APM video 150. An example of generation of an APMvideo 150 and a signal representation in the form of a monophasic actionpotential (MAP) is described in U.S. Pat. No. 8,165,666, which isincorporated herein by reference in its entirety. In particular, FIG. 11of the '666 patent illustrates an APM video 150 of MAPs. Other signalsof value include noise-free unipolar electrograms and processed unipolarelectrograms. Similarly, other systems and methods can reconstructcardiac or biological activation information to include activationtimes, phase information and onset.

The APM video 150 may be generated by systems and methods that candisplay process or reconstruct cardiac or biological electricalinformation over time to generate a dynamic video representation ofactivation information, electrical activity, rotational activity and/ora core associated with the rotational activity, focal activity and/orthe origin from where centrifugal activation emanates.

In one embodiment or aspect, rotational activation is indicated fromphase mapping by a phase singularity, in which the dynamic activationinformation may exhibit rotational motion. The APM video 150 in thiscase may also display an indicator of a phase singularity, such as awhite dot, that may be determined by calculations performed per frame.Each frame displays information based on measurements made at the timeof the frame. The degree of confidence in each rotational driver in thisembodiment is indicated by the persistence of a phase singularity overtime. Singularities detected for only a short amount of time maydisplayed in only a few frames so that the visual indication is notvisible, is barely visible, and/or quickly disappears. When there ispersistence, the frame-by-frame rotational motion may be visible anddetectable to a viewer.

FIG. 2 illustrates a phase-time curve 200 generated from voltage-timedata (activation-time data) of MAP signals obtained during the heartrhythm disorder, for one preferred embodiment of rotational driverdetection via phase mapping. The phase-time data and phase time curve200 are generated by processing MAP signals, including converting thevoltage-time data represented by MAPs into the phase-time data withnoise-reduction and further processing of the data. The voltage-time tophase-time data conversions used for generating curve 200 may beperformed by multiplying a normalized voltage of sampled data pointsalong the MAP signal (which may be approximated) by 2π. The phase-timedata is plotted on x-y axes corresponding to time and phase,respectively. Voltage-time to phase-time data conversions are understoodby a person having skill in the art. The representation used in thepresent example is a sawtooth approximation.

The approximation may be performed on the MAP signal before theconversion or after the conversion. The phase-time data shown in FIG. 2approximates the MAP signal (that actually has four distinct phases, asshown in FIG. 3, but approximates a triangle) with a straight line. Aportion of a MAP signal extending between a detected activation onsetand a detected beginning of repolarization is approximated with astraight line. Similarly, a portion of the MAP signal extending from thebeginning of repolarization to a next activation onset time isapproximated with a straight line. Either or both approximations may beused.

FIG. 3 shows an example phase-time curve 300 that is also converted fromvoltage-time data (activation-time data) associated with MAP signals andthen converted to phase-time data, as described above. As shown, anapproximation is not used to generate the phase-time data represented byphase-time curve 300.

The computing device 116 generates, accesses, or receives phase-timedata, phase-time curves 200, 300 and/or the APM 150. The APM 150spatially arranges MAPs on a display that may be a two-dimensional orthree-dimensional display, such as a model shaped as the heart 120. Thespatial arrangement is relative to the physical sensor locations 104 inrelation to the heart 120. Similarly, other systems and methods that canreconstruct cardiac or biological electrical information to providerepresentations of cardiac electrical activity having activation onsetinformation (activation-time data) may be used to generate the APM video150.

FIG. 4 provides an example two-dimensional APM frame 400 of a series offrames (e.g., an APM video 150) that correspond to sequential,evenly-spaced time increments (e.g., every millisecond (msec) or every10 msec) in a time interval. The time interval can be two-ten seconds,or a different interval. Each APM frame 400 can be generated by samplingmultiple MAP signals at time t of the time interval.

APM frame 400 includes a grid 402 having an electrode reference 404labeled 1-8 and a spline reference 405 labeled A-H. The electrodereference 404 and spline reference 405 have 64 intersecting elements,also referred to as sensor elements, which correspond to respectivesensors 104 of the array of sensors (e.g., 64 sensors). Four examplesensor elements 406, 408, 410, 412 correspond to respectiveintersections on the grid 402 (1-8, A-H), and further correspond torespective sensors 104 of the array of sensors. Specifically, the sensorelements 406, 408, 410, 412 are located on grid 402 at intersectingelements that may be labeled (6, G), (6, H), (5, H), and (5, G),respectively.

Grid 402 is segmented into a plurality of areas, with each area definedor bounded by at least three sensor elements. The areas are configuredas polygons (e.g., a triangle, rectangle, or square), and some cases cancover the entire grid 402. The sensor elements that define each area arepositioned at vertices of the area. An example area 414 is a squarehaving vertices at intersecting elements that may be labeled (6, G), (6,H), (5, H), and (5, G). Area 414 is defined by sensor elements 406, 408,410, 412 that are positioned at the four vertices of a square (G-H,6-5). In the example shown, the entire grid 402 is covered bycontiguous, non-overlapping square areas, with each square area beingbounded or defined by four sensor elements. Area 414 corresponds to anarea of the heart 120 defined or bounded by the sensors 104, whichcorrespond to the sensor elements 406, 408, 410, 412. In anotherembodiment, the areas may overlap. Similarly, an example second area isdefined by sensor elements 416, 418, 420, 422, which correspond torespective sensors 104.

The sensor elements of the APM frame 400 are assigned a gray-scale levelthat corresponds to the voltage (or charge) of the MAP signals. Thegray-scale levels for elements located between the sensor elements 406,408, 410, 412 may be determined using interpolation (e.g., based on therepresentative MAP signals). The '666 patent and U.S. patent applicationSer. No. 13/081,411, which are incorporated herein by reference in theirentirety, describe systems and methods to generate a series of APMframes.

A series of APM frames 400 may be displayed in a sequence, e.g., as avideo stream (APM video 150). A viewer may be able to see changes in therepresented voltage (or charge) depicted over time. This approach maydisplay either a rotational or focal driver. In this example, the changein voltage has a rotational pattern over time, indicating that a phasesingularity has been sensed by sensors 104. Notably, the displayedrotational patterns may not be indicative of a phase singularity that isassociated with a cardiac rhythm disorder. Rotational patterns lesslikely to indicate drivers of heart rhythm disorders are inconsistent,fleeting, and/or non-persistent; they may change rotational directionand/or have an insubstantial degree of rotation. In fact, some of therotational patterns may not be displayed for a sufficient number offrames to be visible to a viewer, whereas other rotational patterns maybe visible, but may then disappear. Despite all of this, the APM video150 of APM frames 400 can provide useful information to a surgeon,including dynamic changes over time and the rotational patterns on thegrid 402.

In one embodiment or aspect, the present disclosure provides a systemand method that sums, for all of the time increments in a time interval,rotational activity associated with each area on the grid 402. The totalsum is indicative of a phase singularity located at that area. Excludedfrom the sum, however, is rotational activity that occurs in oppositedirections at the same area and rotational activity that has aninsubstantial degree of rotation (e.g., satisfies criteria in accordancewith the disclosed method described below). The sum is recorded by arotational counter associated with each area of the grid 402. Therotational counter is modified, e.g., incremented, each time there isrotational activity having a substantial degree of rotation in theassociated area. When the time interval is ended, the magnitude of therotational counter associated with each area of the grid 402 indicatesthe existence and degree of persistence of phase singularities at eacharea of the grid 402.

Turning now to FIGS. 5 and 6, a method is described for determiningwhether rotational activity at time t has a substantial degree ofrotation that would warrant incrementing the rotational counter. Foreach time t, a phase sum is calculated for each area on grid 402. Thephase sum is calculated by determining a shortest path between asequence of the sensor elements (406, 408, 410, 412) beginning andending at a first sensor element of the sequence, calculating a phasedifference between the sensor elements in the sequence using a shortestpath, and summing the phase differences. The calculated phase sum resultmay be 0, 2π, or −2π. Phase sum=0 indicates insufficient rotationalactivity for incrementing the rotational counter and indicates that nonet rotation is present. Phase sum=2π or −2π indicates that therotational counter should be updated, e.g., incremented or decremented,respectively, and indicates that rotation occurs, with the positive ornegative sign indicative of a clockwise or counterclockwise direction ofrotation (e.g., depending on a convention selected). The selectedconvention can be that a positive value is associated with acounterclockwise path, and a negative value is associated with aclockwise path. The selected convention can also be the reversed, i.e.,the negative value is associated with the counterclockwise path, and thepositive value is associated with the clockwise path.

FIG. 5 illustrates an example method for calculating phase sum at time tfor the area 414 defined by sensor elements 406, 408, 410, and 412 inFIG. 4. A unit circle 502 having radius=1 is provided. Sensor elements406, 408, 410, and 412 are disposed on the circumference of the unitcircle 502 in accordance with a phase associated with each of therespective sensor elements 406, 408, 410, and 412. The phase associatedwith each sensor element 406, 408, 410, and 412 is determined from thephase at time t along the corresponding phase-time curve, e.g.,phase-time curves 200 or 300.

Any sensor element may be selected to be the first sensor element. Thesensor elements are then processed in a selected sequence. The sequencemay be based on the position of sensor elements 406, 408, 410, and 412on grid 402, by proceeding in a counterclockwise or clockwise directionaround area 414 among the sensor elements in accordance with theirarrangement on grid 402, beginning with the first selected sensorelement and ending with the first sensor element. In this example,sensor elements are ordered as 406, 408, 410, 412. Sensor element 406 isselected to be the first sensor element.

The shortest path is determined between the first sensor element 406 andthe second sensor element 408. The path 504 in the counterclockwisedirection is shorter than an alternative path in the clockwisedirection. Therefore, path 504 is determined to be the shortest pathbetween sensor elements 406 and 408.

The phase difference 512 between the sensor elements 406 and 408 forshortest path 504 is determined. The phase difference 512 is assigned apositive value because the shortest path from sensor element 406 tosensor element 408 is in a counterclockwise direction based on theselected convention.

The shortest path and phase difference are similarly determined for eachof the sensor element pairs 408 and 410, 410 and 412, and 412 and thefirst sensor element 406. The shortest paths, respectively, are 506,508, and 510, all in the counterclockwise direction. Thus, therespective phase differences 514, 516, and 518 are all positive. Thefour phase differences 512-518 are summed to determine the phase sum.Since the entire circumference of the unit circle is traversed in thecounterclockwise direction along the shortest paths 504-510, all of thephase differences are positive. Phase sum=2π, which indicates thepossible presence of a rotational driver.

The example in FIG. 5 illustrates that there is an indication of arotational driver when a full circle around the unit circle 502 iscompleted by following the shortest paths between sensor elements 406,408, 410, 412 disposed on the unit circle 502, including back to thefirst sensor element 406. When the rotation between the sensors 104 isin one direction, the phase differences are all positive or all negativeand do not cancel each other out. This results in a phase sum=2π, whichindicates that the rotational activity measured at the correspondingsensors 104 is consistent with a rotational driver of the heart rhythmdisorder.

FIG. 6 illustrates another example for calculating phase at time t foranother area of the grid 402. A unit circle 602 having radius=1 isprovided with sensor elements 416, 418, 420, and 422 disposed on thecircumference of unit circle 602.

The shortest path 604 is determined between the first sensor element 416and the second sensor element 418. The path in the clockwise directionis shorter than an alternative path in the counterclockwise direction.Therefore, the shortest path is determined to be the shortest path 604.

The phase difference 612 between the sensor elements 416 and 418 for theshortest path 604 is determined. The phase difference 612 is assigned anegative value because the shortest path 604 from sensor element 416 tosensor element 418 traverses the circumference of the unit circle 602 ina clockwise direction based on the selected convention.

The shortest path and phase difference are similarly determined for eachof sensor element pairs 418 and 420, 420 and 422, and 422 and the firstsensor element 416. The shortest paths, respectively, are 606, 608, and610. Shortest path 606 is directed in a clockwise direction. Therefore,phase difference 614 has a negative value. Shortest paths 608 and 610are in a counterclockwise direction. Therefore, phase differences 616and 618 have positive values. The phase differences 612 and 614 cancelout the phase differences 616 and 618, since they are equal in magnitudewhen summed, but opposite in direction. Thus, the sum of phasedifferences 612-618 is zero (0), which indicates the absence of a phasesingularity at this area.

The example in FIG. 6 illustrates that there is no indication ofrotation when a full circle around the unit circle 602 cannot becompleted by following the shortest paths between sensor elements 416,418, 420, 422 disposed on the unit circle 602, including back to thefirst sensor element 416. When the rotation between the sensors 104 isin different directions (clockwise and counterclockwise), then somephase differences are positive and some are negative, cancelling eachother out. This results in a phase sum=0, which indicates that therotational electrical activity measured at the corresponding sensors 104is insufficient to indicate a rotational driver.

FIGS. 7 and 8 provide example flow diagrams that describe an examplemethod 700 to process activation-time data for a time interval TI inorder to detect rotational activation that is sufficiently significantand persistent to indicate the existence of a source of a cardiac rhythmdisorder.

Importantly, the flowcharts outline a method and a system to sum indexesof rotational activation (detected for instance, via singularities orangles of rotation) as well as focal drivers (detected, for instance,from centrifugal activation). This is important since both may coexist,and because the principle of centrifugal activation from a source mayapply whether the driver associated with the source is focal orrotational. Thus, all analyses included in this specification includeeither analyses (summation) of indexes of rotational activation, indexesof centrifugal activation (that may be centripetal if the source moves)or a combination over time.

The method further includes generating a visual quantitative display ofthe persistence of drivers of sources associated with heart rhythmdisorders. The heat map indicates locations in grid 402 associated withpersistent rotations and/or the degree of the persistence. Heat mapdisplays the areas of grid 402 and assigns each area a visual indication(e.g., color, shade, or intensity) that indicates the magnitude of therotational counter associated with that area. When the rotationalcounter associated with an area is incremented or decremented by 1, thevisual indication associated with that area is increased or decreased,respectively, by one unit to show the change in the rotational counter.

A unit of a visual indication may be for example, a spectral unit, e.g.,along the rainbow spectrum, such as wherein red is at the high end andviolet is at the low end, a shade of gray unit; or an intensity unit.These units can be dimensionless, can indicate a ratio relative to abaseline uniform (non-rotational) propagation field, or can have otherdimensions. This will vary with the specific heart rhythm disorder andsignal source under consideration, but may include degrees (radians) orpersistent rotation, a ratio (%) of persistence across a number ofcycles, a correlation value (dimensionless) and other dimensions.

The heat map may include a single map or a video including a series ofmaps. The heat map may be displayed independently or overlaid (e.g.,superimposed) over another map, such as an APM frame or a structural mapof a corresponding biological structure, e.g., the heart 120. When theheat map is overlaid over an APM frame, such as being overlaid over anAPM video 150, they are synchronized to display information relating tothe same time increment. Additionally, they are spatially consistentwith one another in reference to the biological structure (e.g., heart120).

At step 702, activation-time data is accessed or received. Theactivation-time data may be accessed in real time during a procedure inwhich sensors 104 generate sensing data, or after a procedure iscompleted. The activation-time data may be accessed from a computingdevice 116 or a remote device, such as via a wired or wirelesscommunication. Moreover, in some embodiments or aspects, theactivation-time data thus accessed or received can be converted tophase-time data in accordance with description in reference to FIGS. 2and 3 hereinabove.

At initialization step 704, a time counter, t, is initialized by settingt=0. Also, the rotational counter associated with each area of grid 402is initialized by setting each rotational counter=0. Additionally, theheat map is initialized by setting the visual indication of each area ofgrid 402 to a neutral visual indication that indicates rotationalcounter=0 for that area.

At step 706, an outer loop 708 commences to iteratively process all timeincrements within time interval TI. Step 706 increments t by apredetermined time increment which, in the current example, is one (1)msec. At step 710, an inner loop 712 commences to iteratively processeach area included in grid 402 (shown in FIG. 4). Accordingly, loops 708and 712 process all areas of grid 402 for each incremental time t.

At step 710, a next unprocessed area of grid 402 is selected. For thefirst pass through the inner loop 712, a first area is selected. Forexample, the first area may be selected to be the square area bounded bysensor elements 104 located in the upper left hand corner of grid 402 atgrid intersections (8, D), (8, E), (7, E), and (7, D). In someembodiments or aspects, the activation-time data can be converted tophase-time data for the selected area in accordance with description inreference to FIGS. 2 and 3 hereinabove.

The second selected area may also be adjacent to the previously selectedarea and so on. Accordingly, in the example shown, inner loop 712 isprocessed forty-nine (49) times until each of the forty-nine (49) areasprovided in grid 402 is processed for the current time t. The order ofprocessing the areas may be predefined, but is not limited to anyparticular order.

As an example, area 414 illustrated in FIG. 4 is selected forprocessing. The selected area 414 is processed at step 800 to calculatean index of driver activity for the selected area 414. Accordingly, thegrid intersections for sensor elements 406-412 that define the selectedarea 414 are provided as input to step 800. The index of driver activityfor the selected area 414 is determined at step 800. For example, theindex of driver activity is calculated using the analysis of FIGS. 5 and6 in accordance with phase-time data converted in accordance with FIGS.2 and 3. Step 800 outputs the index of driver activity for the selectedarea 414, after which control passes to determination step 714. Step 800is described below in greater detail with respect to FIG. 8.

At step 714, a determination is made whether driver activity is over anentire cycle. If the entire cycle is driven by the driver, then controlpasses to step 716. If the entire cycle is not driven by the driver,then control passes to step 720.

At step 716, a rotational counter associated with the currently selectedarea is incremented by a count of one. At step 718, the heat map isupdated by increasing the visual indication associated with the selectedarea by one unit. Then, control passes to step 724, the end ofinner-loop 712.

At step 720, the rotational counter is decremented by a count of one. Atstep 722, the heat map is updated by decreasing the visual indicationassociated with the selected area by one unit. Then, control passes tostep 724, the end of inner-loop 712.

At step 724, a determination is made whether all areas were processedfor time=t. If not, execution passes to step 710, and another pass ofinner-loop 712 is processed for the next area until all of the areas ofgrid 402 have been processed. If the determination at step 724 is thatall areas have been processed for time=t, then execution proceeds tostep 726, the end of outer-loop 708, to determine whether all frames forinterval TI were processed (e.g., t>=TI).

If the determination at step 726 is that t<TI, meaning that there aremore time frames (increments) to process for interval TI, then controlreturns to step 706 and a next pass of outer-loop 708 is performed forthe next time increment. If the determination at step 726 is that t=TI,meaning that all of the frames in interval TI have been processed, thenouter-loop 708 is terminated, and control passes to step 728, at whichthe method 700 ends.

In operation, during each iteration of outer-loop 708 at time t, allareas are processed and the rotational counter and the visual indicationof the heat map associated with each area are updated and summed. Thus,with each subsequent iteration of outer-loop 708, the rotational counterassociated with each area is updated by incrementing or decrementing therotational counter, depending on the rotational direction. When apossible rotational driver having the same rotational direction isdetected in an area in many iterations of outer-loop 708, the rotationalcounter associated with that area is successively incremented (ordecremented, depending upon polarity) and achieves a relatively highmagnitude in the positive or negative direction, indicating the presenceof persistent rotational activation in a counterclockwise or clockwisedirection at the area.

On the other hand, when opposite rotational directions occur duringdifferent iterations of outer-loop 708, the rotational counter isincremented and then decremented (or vice versa), cancelling out anincrease in magnitude (herein referring to the rotational counterabsolute value), indicating that a persistent rotational driver does notexist at the area. Accordingly, the magnitude of the rotational counterassociated with each area is indicative of the persistence of rotationin a consistent rotational direction.

In some embodiments or aspects, the heat map may include only the finalframe, and/or the final magnitude of the rotational counter for eacharea may be reported. The magnitude of each rotational counter indicateswhether rotation occurs in the associated area and its degree ofpersistence. The final magnitude of the rotational counter associatedwith the respective area may be compared to a predetermined threshold.If the rotational counter exceeds the threshold, a determination may bemade that persistent rotation occurs in the associated area. While thefinal magnitude of the rotational counter provides static quantitativeinformation, the final heat map frame provides static qualitative visualinformation about the existence and persistence of rotational patterns.

In other embodiments or aspects in which the method 700 is performed,when the phase-time data for the entire time interval and/or all of theareas is available before beginning execution of step 704, some or allof the execution steps in the example method 700 may be performed in adifferent order, serially, in parallel, or a combination thereof, asopposed to iteratively. Steps associated with different frames and/ordifferent areas may be performed in a different order, serially, inparallel, or a combination thereof. The method 700 ends at step 728.

With reference to FIG. 8, an example method is shown for executing step800 in FIG. 7. The method processes an area and determines an index ofdriver activity for the area. At input step 801 the identification ofthe area selected at step 710 in FIG. 7 is provided as input. The inputincludes identification of the sensor elements that define the selectedarea. In the present example, the selected area is area 414 which isdefined by the sensor elements 406-412.

At step 802, the index of driver activity is initialized to 0. At step804, a loop 806 commences for iteratively selecting, in a sequence,sensor elements 406-412 that define the area 414, for example. In thecurrent example, sensor element 406 is selected for the first passthrough loop 806. Sensor elements 408, 410, and 412 are selectedsequentially for subsequent respective passes through loop 806. Theexample sequence describes a counterclockwise path around area 414.Other sequences may be selected.

At step 808, the index of driver activity is determined based on lastand next vertexes of a selected area, e.g., between a selected sensorelement and the next sensor element in the sequence, moving from theselected sensor element to the next sensor element in a selecteddirection (e.g., clockwise or counterclockwise). It is noted that thesame selected direction is used for all iterations of loop 806. In thepresent example, during the first pass through loop 806, the index ofdriver activity between sensor elements 406 and 408 is determined.During the second, third and fourth passes, respectively, the index ofdriver activity between sensor elements is determined. At step 810, adetermination is made as to whether an arc of rotation continues in thesame direction. If no, step 812 is executed to adjust the index ofdriver activity, e.g., subtracting a value from the index of the driveractivity. If yes, step 814 is executed to adjust the index of driveractivity, e.g., adding a value to the index of the driver activity.

At step 818, end of loop 806, a determination is made whether allvertexes (e.g., sensor elements 406-412 were processed for the selectedarea 414. If not, control returns to step 804 to select the next sensorelement in the sequence and to execute loop 806 with the newly selectedsensor element. After the final iteration of loop 806, at step 818 adetermination is made whether all of the sensor elements have beenselected and processed. If so, the index of driver activity is output atstep 820 and control passes to step 714 of FIG. 7.

Now with reference to FIG. 7, the heat map generated by the computingdevice 116 is overlaid on an APM frame. The heat map may include aseries of frames that correspond to the time increments associated witheach iteration of outer-loop 708. The heat map uses a visual indication,such as color, intensity, or shades of gray to indicate the magnitude ofthe rotational counter associated with each area of grid 402. The higherthe magnitude of the rotational counter, the stronger the persistence ofdetected rotational activation areas.

Different colors or shades of gray may be assigned to various rotationalcounter magnitudes. The colors and shades of the heat map may betranslucent so that when overlaid over another map, graphic, text, orthe like, the underlying information may be visible. In a multicolorconfiguration, for example, warm colors may be assigned to the higherrotational counter magnitudes, and cool colors may be assigned to thelower rotational counter magnitudes (e.g., based on the rainbowspectrum), with red indicating the highest magnitude and purplerepresenting the lowest. In a gray-scale configuration, for example,light shades may be assigned to the higher magnitudes and dark shadesmay be assigned to the lower magnitudes, with white indicating thehighest magnitude and black representing the lowest magnitude.

In the current example, a single color is used, such as red, wherein theintensity of the color increases with the magnitude of the rotationalcounter. When the rotational counter=0 the color is not displayed.

As iterations of outer-loop 708 are processed and the rotational counteris updated, the heat map is updated, frame by frame. Thus, each frame ofheat map represents a summation of the previous frames. Throughout thesummation, an increase of magnitude of the rotational counter indicatesexistence of and persistence of a detected rotational pattern. When step728 is reached, a final frame of the heat map has been generated and theheat map is complete. The final frame shows the summation of all theprevious frames and graphically shows persistent rotations, theirlocation on the grid 402, and the degree of their persistence.

The displayed heat map indicates the location of a persistent rotationalpattern (driver) to a viewer, e.g., a surgeon. The surgeon may use thatinformation to identify a source associated with a cardiac rhythmdisorder. Accordingly, the surgeon may treat cardiac tissue at thesource, and/or the rotational pattern (driver) that drives the source,or within a possible margin of tissue to suppress or eliminate thecardiac rhythm disorder.

The series of frames of the heat map may be stored and replayed. Sincethe information is summed for all areas of grid 402 with each iterationof outer-loop 708, as the series of frames of the heat map video isreplayed, the visual indications of persistence are dynamic, withpersistent rotation shown increasing in intensity, and fleeting rotationor noise either not visible, or visible for a short duration and thendisappearing or fading.

The grid 402 may be normalized with respect to a preference value. Thepreference value may be used to set a most significant value to one (1),with the others assuming a range between zero (0) and one (1).Alternatively, the grid 402 may be normalized with respect to the timeanalyzed, reflecting a percentage of time during which detected phasesingularities are present.

FIG. 9 shows a frame 900 that includes a heat map frame 902 overlaidover an APM frame 903. APM frame 903 may be a single stand-alone frameor may belong to a series of APM frames, e.g., a video 150. When theheat map 902 video is overlaid over an APM video, the maps can besynchronized so that the frames 902 and 903 correspond to the same timeincrement. Alternatively, they may be unsynchronized.

The example APM 903 includes an area of electrical activity 906 thatmoves about a central point, as seen when playing back previous frames.Based on information gathered in a single frame, the central point hasbeen identified as a region having repeating activation indicated by awhite dot 904. The heat map 902 includes an area 908 that includes areas910, 912, 914 of varying intensity, listed here from least to mostintense. The area 908 indicates that the rotational counter associatedwith that portion of heat map 902 has been incremented, with theintensity of the red area 908 increasing in areas 912 and 914 inaccordance with the magnitude of the rotational counter. The mostintense area 914 corresponds to the highest calculated magnitude of therotational counter. The highest calculated magnitude of the rotationalcounter and the most intense area 914 may indicate the center (driver)of the electrical activity 906 and be indicative of the source of acardiac rhythm disorder. Here, the most intense area 914 is located nearwhite dot 904 of the APM 903. Accordingly, the white dot 904 of the APM903 is consistent with the intense red area 914 of the heat map 902.

An example area 918 is shown on heat map 902, with its boundariesindicated by dotted lines. The area 918 may include smaller elements920. The visual indication associated with the area 918 may vary withinthe area 918, with different elements 920 appearing to have a differentvisual indication. Methods and calculations, such as interpolation, maybe used to vary the visual indication of different elements 920 withinarea 918. Additionally, the appearance of the visual indication of thetwo elements 920 having the same visual indication may differ due to theunderlying image, e.g., the APM 903.

The heat map 902 provides a summation of information that builds overthe course of the video to display persistent patterns, and filters outevents that do not have a significant amount of associated rotation. Thecombination of information provides the viewer with a combination ofrobust information, dynamic information and locational information.

Additionally or alternatively, the heat map 902 may be overlaid orsuperimposed on an image of the sensor locations and/or the anatomywhere the sensors 104 are positioned. This combination of images mayprovide additional locational information relating the location of thepersistent phase singularities relative to the location of the sensors104.

FIG. 10 is a block diagram of an illustrative embodiment of a generalcomputing system 1000. The computing system 1000 can include a set ofinstructions that can be executed to cause the computing system 1000 toperform any one or more of the methods or computer based functionsdisclosed herein. The computing system 1000, or any portion thereof, mayoperate as a standalone device or may be connected, e.g., using anetwork 1024 or other connection, to other computing systems orperipheral devices.

The computing system 1000 may also be implemented as or incorporatedinto various devices, such as a personal computer (PC), a tablet PC, apersonal digital assistant (PDA), a mobile device, a palmtop computer, alaptop computer, a desktop computer, a communications device, a controlsystem, a web appliance, or any other machine capable of executing a setof instructions (sequentially or otherwise) that specify actions to betaken by that machine. Further, while a single computing system 1000 isillustrated, the term “system” shall also be taken to include anycollection of systems or sub-systems that individually or jointlyexecute a set, or multiple sets, of instructions to perform one or morecomputer functions.

As illustrated in FIG. 10, the computing system 1000 may include aprocessor 1002, e.g., a central processing unit (CPU), agraphics-processing unit (GPU), or both. Moreover, the computing system1000 may include a main memory 1004 and a static memory 1006 that cancommunicate with each other via a bus 1026. As shown, the computingsystem 1000 may further include a video display unit 1010, such as aliquid crystal display (LCD), an organic light emitting diode (OLED), aflat panel display, a solid state display, or a cathode ray tube (CRT).Additionally, the computing system 1000 may include an input device1012, such as a keyboard, and a cursor control device 1014, such as amouse. The computing system 1000 can also include a disk drive unit1016, a signal generation device 1022, such as a speaker or remotecontrol, and a network interface device 1008.

In a particular embodiment or aspect, as depicted in FIG. 10, the diskdrive unit 1016 may include a machine-readable or computer-readablemedium 1018 in which one or more sets of instructions 1020, e.g.,software, can be embedded, encoded or stored. Further, the instructions1020 may embody one or more of the methods or logic as described herein.In a particular embodiment or aspect, the instructions 1020 may residecompletely, or at least partially, within the main memory 1004, thestatic memory 1006, and/or within the processor 1002 during execution bythe computing system 1000. The main memory 1004 and the processor 1002also may include computer-readable media.

In an alternative embodiment or aspect, dedicated hardwareimplementations, such as application specific integrated circuits,programmable logic arrays and other hardware devices, can be constructedto implement one or more of the methods described herein. Applicationsthat may include the apparatus and systems of various embodiments oraspects can broadly include a variety of electronic and computingsystems. One or more embodiments or aspects described herein mayimplement functions using two or more specific interconnected hardwaremodules or devices with related control and data signals that can becommunicated between and through the modules, or as portions of anapplication-specific integrated circuit. Accordingly, the present systemencompasses software, firmware, and hardware implementations.

In accordance with various embodiments or aspects, the methods describedherein may be implemented by software programs tangibly embodied in aprocessor-readable medium and may be executed by a processor. Further,in an exemplary, non-limited embodiment or aspect, implementations caninclude distributed processing, component/object distributed processing,and parallel processing. Alternatively, virtual computing systemprocessing can be constructed to implement one or more of the methods orfunctionality as described herein.

It is also contemplated that a computer-readable medium includesinstructions 1020 or receives and executes instructions 1020 responsiveto a propagated signal, so that a device connected to a network 1024 cancommunicate voice, video or data over the network 1024. Further, theinstructions 1020 may be transmitted or received over the network 1024via the network interface device 1008.

While the computer-readable medium is shown to be a single medium, theterm “computer-readable medium” includes a single medium or multiplemedia, such as a centralized or distributed database, and/or associatedcaches and servers that store one or more sets of instructions. The term“computer-readable medium” shall also include any tangible medium thatis capable of storing or encoding a set of instructions for execution bya processor or that cause a computing system to perform any one or moreof the methods or operations disclosed herein.

In a particular non-limiting, example embodiment or aspect, thecomputer-readable medium can include a solid-state memory, such as amemory card or other package, which houses one or more non-volatileread-only memories. Further, the computer-readable medium can be arandom access memory or other volatile re-writable memory. Additionally,the computer-readable medium can include a magneto-optical or opticalmedium, such as a disk or tapes or other storage device to capture andstore carrier wave signals, such as a signal communicated over atransmission medium. A digital file attachment to an e-mail or otherself-contained information archive or set of archives may be considereda distribution medium that is equivalent to a tangible storage medium.Accordingly, any one or more of a computer-readable medium or adistribution medium and other equivalents and successor media, in whichdata or instructions may be stored, are included herein.

In accordance with various embodiments or aspects, the methods describedherein may be implemented as one or more software programs running on acomputer processor. Dedicated hardware implementations including, butnot limited to, application specific integrated circuits, programmablelogic arrays, and other hardware devices can likewise be constructed toimplement the methods described herein. Furthermore, alternativesoftware implementations including, but not limited to, distributedprocessing or component/object distributed processing, parallelprocessing, or virtual machine processing can also be constructed toimplement the methods described herein.

It should also be noted that software that implements the disclosedmethods may optionally be stored on a tangible storage medium, such as amagnetic medium, such as a disk or tape; a magneto-optical or opticalmedium, such as a disk; or a solid state medium, such as a memory cardor other package that houses one or more read-only (non-volatile)memories, random access memories, or other re-writable (volatile)memories. A stored digital file attachment to e-mail or otherself-contained information archive or set of archives is considered adistribution medium equivalent to a tangible storage medium.Accordingly, a tangible storage medium or distribution medium as listedherein, and other equivalents and successor media, in which the softwareimplementations herein may be stored, are included herein.

Thus, a system and method to define a rational source associated with abiological rhythm disorder, such a heart rhythm disorder, has beendescribed herein. Although specific example embodiments or aspects havebeen described, it will be evident that various modifications andchanges may be made to these embodiments or aspects without departingfrom the broader scope of the invention. Accordingly, the specificationand drawings are to be regarded in an illustrative rather than arestrictive sense. The accompanying drawings that form a part hereof,show by way of illustration, and not of limitation, specific embodimentsor aspects in which the subject matter may be practiced. The embodimentsor aspects illustrated are described in sufficient detail to enablethose skilled in the art to practice the teachings disclosed herein.Other embodiments or aspects may be utilized and derived therefrom, suchthat structural and logical substitutions and changes may be madewithout departing from the scope of this disclosure. This DetailedDescription, therefore, is not to be taken in a limiting sense, and thescope of various embodiments or aspects is defined only by the appendedclaims, along with the full range of equivalents to which such claimsare entitled.

Such embodiments or aspects of the inventive subject matter may bereferred to herein, individually and/or collectively, by the term“invention” merely for convenience and without intending to voluntarilylimit the scope of this application to any single invention or inventiveconcept if more than one is in fact disclosed. Thus, although specificembodiments or aspects have been illustrated and described herein, itshould be appreciated that any arrangement calculated to achieve thesame purpose may be substituted for the specific embodiments or aspectsshown. This disclosure is intended to cover any and all adaptations orvariations of various embodiments or aspects. Combinations of the aboveembodiments or aspects, and other embodiments or aspects notspecifically described herein, will be apparent to those of skill in theart upon reviewing the above description.

The Abstract is provided to comply with 37 C.F.R. § 1.72(b) and willallow the reader to quickly ascertain the nature and gist of thetechnical disclosure. It is submitted with the understanding that itwill not be used to interpret or limit the scope or meaning of theclaims.

In the foregoing description of the embodiments or aspects, variousfeatures are grouped together in a single embodiment for the purpose ofstreamlining the disclosure. This method of disclosure is not to beinterpreted as reflecting that the claimed embodiments or aspects havemore features than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter lies in less than allfeatures of a single disclosed embodiment or aspect. Thus the followingclaims are hereby incorporated into the Detailed Description, with eachclaim standing on its own as a separate example embodiment or aspect. Itis contemplated that various embodiments or aspects described herein canbe combined or grouped in different combinations that are not expresslynoted in the Detailed Description. Moreover, it is further contemplatedthat claims covering such different combinations can similarly stand ontheir own as separate example embodiments or aspects, which can beincorporated into the Detailed Description.

The invention claimed is:
 1. A method of identifying an area of a humanheart, the area associated with control of a source of a cardiac rhythmdisorder of the human heart, the method comprising: processing aplurality of cardiac signals associated with sensors arranged spatiallyin relation to the area of the heart to determine at least one sequenceof activation in relation to the sensors over a time interval, the areacomprising a first region and a second region associated with thesource; determining a rotational direction of the at least one sequenceof activation; and identifying the first region as associated withcontrolling the second region when the at least one sequence ofactivation continues to rotate in the rotational direction with asubstantial degree of rotation over the time interval as indicated by arotational counter incremented in excess of a threshold.
 2. The methodof claim 1, wherein the sensors define vertices of the area of theheart.
 3. The method of claim 2, wherein the area comprises a pluralityof areas of the heart defined by the vertices, the plurality of areasassociated with controlling the source of the cardiac rhythm disorder.4. The method of claim 1, wherein the method further comprisesgenerating an indicator associated with the area of the heart ascontrolling the source.
 5. The method of claim 4, wherein the methodfurther comprises corresponding the indicator to the sensors arrangedspatially in relation to the area of the heart.
 6. The method of claim5, wherein corresponding the indicator to the sensors arranged spatiallyin relation to the area of the heart comprises overlaying the indicatorover a representation of the plurality of cardiac signals.
 7. The methodof claim 1, wherein determining the rotational direction of the at leastone sequence of activation further comprises: determining arcs ofrotation of the at least one sequence in relation to the sensors overthe time interval; and determining rotational directions of the arcs ofrotation.
 8. The method of claim 7, wherein identifying the area of theheart as associated with controlling the source further comprisesdetermining that the rotational directions of the arcs of rotationcontinue in the rotational direction in excess of the threshold.
 9. Themethod of claim 7, wherein determining a rotational direction of an arcof rotation comprises: selecting a first cardiac signal and a secondcardiac signal from the plurality of cardiac signals; determiningindices of rotational activity among the first cardiac signal and thesecond cardiac signal at a plurality of time points during the timeinterval; and combining the indices of rotational activity to define therotational direction of the arc of rotation.
 10. The method of claim 9,wherein determining an index of rotational activity comprises:calculating a phase difference among the first cardiac signal and thesecond cardiac signal at a time point of the time interval; anddetermining whether the phase difference is less than or equal to afirst phase threshold, or whether the phase difference is greater than asecond phase threshold; incrementing the phase difference by a phasevalue when the phase difference is less than or equal to the first phasethreshold; and decrementing the phase difference by the phase value whenthe phase difference is greater than the second phase threshold.
 11. Themethod of claim 10, wherein combining the indices of rotational activitycomprises summing calculated phase differences, as incremented ordecremented, at the plurality of time points of the time interval. 12.The method of claim 1, wherein the method further comprises: performingprocessing, determining and identifying over a plurality of timeintervals; and determining persistence of the identified area ascontrolling the source when the at least one sequence of activationcontinues to rotate in the rotational direction over the plurality oftime intervals.
 13. The method of claim 12, wherein the method furthercomprises generating an indicator associated with the persistence of theidentified area as associated with controlling the source.
 14. Themethod of claim 13, wherein the method further comprises correspondingthe indicator to the sensors arranged spatially in relation to the areaof the heart.
 15. The method of claim 14, wherein corresponding theindicator to the sensors arranged spatially in relation to the area ofthe heart comprises overlaying the indicator over representations of theplurality of cardiac signals associated with the plurality of timeintervals.
 16. A system to identify an area of a human heart, the areaassociated with control of a source of a cardiac rhythm disorder of thehuman heart, the system comprising: a processing device; and a memorydevice to store a plurality of instructions that, when executed by theprocessing device, cause the processing device to perform operationscomprising: processing a plurality of cardiac signals associated withsensors arranged spatially in relation to the area of the heart todetermine at least one sequence of activation in relation to the sensorsover a time interval, the area comprising a first region and a secondregion associated with the source; determining a rotational direction ofthe at least one sequence of activation; and identifying the firstregion as associated with controlling the second region when the atleast one sequence of activation continues to rotate in the rotationaldirection with a substantial degree of rotation over the time intervalas indicated by a rotational counter incremented in excess of athreshold.
 17. The system of claim 16, wherein the sensors definevertices of the area of the heart.
 18. The system of claim 17, whereinthe area comprises a plurality of areas of the heart defined by thevertices, the plurality of areas associated with controlling the sourceof the cardiac rhythm disorder.
 19. The system of claim 16, wherein theoperations further comprise generating an indicator associated with thearea of the heart as controlling the source.
 20. The system of claim 19,wherein the operations further comprise corresponding the indicator tothe sensors arranged spatially in relation to the area of the heart. 21.The system of claim 20, wherein the operations further compriseoverlaying the indicator over a representation of the plurality ofcardiac signals.
 22. The system of claim 16, wherein the operations todetermine the rotational direction of the at least one sequence ofactivation comprise: determining arcs of rotation of the at least onesequence in relation to the sensors over the time interval; anddetermining rotational directions of the arcs of rotation.
 23. Thesystem of claim 22, wherein the operations to identify the area of theheart as associated with controlling the source comprise determiningthat the rotational directions of the arcs of rotation continue in therotational direction in excess of the threshold.
 24. The system of claim23, wherein the operations to determine a rotational direction of an arcof rotation comprise: selecting a first cardiac signal and a secondcardiac signal from the plurality of cardiac signals; determiningindices of rotational activity among the first cardiac signal and thesecond cardiac signal at a plurality of time points during the timeinterval; and combining the indices of rotational activity to define therotational direction of the arc of rotation.
 25. The system of claim 24,wherein the operations to determine an index of rotational activitycomprise: calculating a phase difference among the first cardiac signaland the second cardiac signal at a time point of the time interval; anddetermining whether the phase difference is less than or equal to afirst phase threshold, or whether the phase difference is greater than asecond phase threshold; incrementing the phase difference by a phasevalue when the phase difference is less than or equal to the first phasethreshold; and decrementing the phase difference by the phase value whenthe phase difference is greater than the second phase threshold.
 26. Thesystem of claim 24, wherein the operation to combine the indices ofrotational activity comprise summing calculated phase differences, asincremented or decremented, at the plurality of time points of the timeinterval.
 27. The system of claim 16, wherein the operations furthercomprise: performing processing, determining and identifying over aplurality of time intervals; and determining persistence of theidentified area as controlling the source when the at least one sequenceof activation continues to rotate in the rotational direction over theplurality of time intervals.
 28. The system of claim 27, wherein theoperations further comprise generating an indicator associated with thepersistence of the identified area as controlling the source.
 29. Thesystem of claim 28, wherein the operations further comprisecorresponding the indicator to the sensors arranged spatially inrelation to the area of the heart.
 30. The system of claim 29, whereinthe operations to correspond the indicator to the sensors arrangedspatially in relation to the area of the heart comprise overlaying theindicator over representations of the plurality of cardiac signalsassociated with the plurality of time intervals.